feat(pygal): implement cat-strip (#2758)

## Implementation: `cat-strip` - pygal

Implements the **pygal** version of `cat-strip`.

**File:** `plots/cat-strip/implementations/pygal.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20601059545)*

---------

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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/cat-strip/implementations/pygal.py

@@ -0,0 +1,89 @@
+""" pyplots.ai
+cat-strip: Categorical Strip Plot
+Library: pygal 3.1.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import pygal
+from pygal.style import Style
+
+
+# Data - Performance scores across different departments
+np.random.seed(42)
+categories = ["Sales", "Engineering", "Marketing", "Support"]
+n_per_category = 25
+
+# Generate realistic performance scores for each department
+data = {
+    "Sales": np.random.normal(75, 12, n_per_category),
+    "Engineering": np.random.normal(82, 8, n_per_category),
+    "Marketing": np.random.normal(70, 15, n_per_category),
+    "Support": np.random.normal(78, 10, n_per_category),
+}
+
+# Clip to realistic range (0-100)
+for cat in data:
+    data[cat] = np.clip(data[cat], 40, 100)
+
+# Create jittered x-positions for strip plot effect
+jitter_width = 0.3
+points_by_category = {}
+for i, cat in enumerate(categories):
+    x_jitter = np.random.uniform(-jitter_width, jitter_width, n_per_category)
+    x_positions = i + x_jitter
+    points_by_category[cat] = list(zip(x_positions, data[cat], strict=False))
+
+# Custom style for large canvas
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#333333",
+    foreground_subtle="#666666",
+    colors=("#306998", "#FFD43B", "#4CAF50", "#E91E63"),
+    title_font_size=72,
+    label_font_size=48,
+    major_label_font_size=42,
+    legend_font_size=42,
+    value_font_size=36,
+    tooltip_font_size=36,
+)
+
+# Create custom x-label formatter to show category names
+x_label_map = {0: "Sales", 1: "Engineering", 2: "Marketing", 3: "Support"}
+
+# Create XY chart (scatter plot)
+chart = pygal.XY(
+    width=4800,
+    height=2700,
+    style=custom_style,
+    title="cat-strip · pygal · pyplots.ai",
+    x_title="Department",
+    y_title="Performance Score",
+    show_legend=True,
+    legend_at_bottom=True,
+    legend_at_bottom_columns=4,
+    stroke=False,
+    dots_size=12,
+    show_x_guides=False,
+    show_y_guides=True,
+    x_label_rotation=0,
+    range=(35, 105),
+    xrange=(-0.5, 3.5),
+    explicit_size=True,
+    print_values=False,
+    x_value_formatter=lambda x: x_label_map.get(int(round(x)), ""),
+)
+
+# Add data for each category as separate series
+for cat in categories:
+    chart.add(cat, points_by_category[cat])
+
+# Set x-axis labels at category positions (integers that will be formatted)
+chart.x_labels = [0, 1, 2, 3]
+chart.x_labels_major = [0, 1, 2, 3]
+
+# Render to PNG and HTML
+chart.render_to_png("plot.png")
+chart.render_to_file("plot.html")

plots/cat-strip/metadata/pygal.yaml

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+library: pygal
+specification_id: cat-strip
+created: '2025-12-30T16:30:49Z'
+updated: '2025-12-30T16:54:25Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20601059545
+issue: 0
+python_version: 3.13.11
+library_version: 3.1.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/cat-strip/pygal/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/cat-strip/pygal/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/cat-strip/pygal/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent jitter implementation using XY chart with calculated x-positions
+  - Clean, professional color scheme with four distinct, accessible colors
+  - Proper title format following pyplots.ai convention
+  - Realistic business context (department performance scores)
+  - Good distribution variation showing different spreads and an outlier
+  - Well-configured custom Style with appropriate font sizes for large canvas
+  weaknesses:
+  - Axis labels lack units (could be "Performance Score (%)" if percentages)
+  - Grid could be slightly more subtle (current alpha via style is acceptable but
+    could improve)